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Exchange rate forecasting using modified empirical mode decomposition and least squares support vector machine

Forecasting exchange rate requires a model that can capture the non-stationary and non-linearity of the exchange rate data. In this paper, empirical mode decomposition (EMD) is combines with least squares support vector machine (LSSVM) model in order to forecast daily USD/TWD exchange rate. EMD is u...

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書誌詳細
主要な著者:	Abdul Rashid, Nur Izzati, Samsudin, Ruhaidah, Shabri, Ani
フォーマット:	論文
出版事項:	International Center for Scientific Research and Studies 2016
主題:	QA75 Electronic computers. Computer science
オンライン･アクセス:	http://eprints.utm.my/id/eprint/71230/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010427055&partnerID=40&md5=631643f0150ef2ece9a4bf0e24623da6
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